In our recent project, we utilized a neural network to predict job trends in Boston, focusing on the correlation between economic indicators like airport traffic and hotel rates and the number of jobs available.
Key Aspects of the Neural Network Analysis:
- Model Composition: Our neural network, comprising multiple layers, was designed to discern complex patterns within economic data.
- Training and Results: After thorough training, the model displayed robust predictive capabilities, with an MSE of 0.2798 and an R2 score of 0.7123, indicating its effectiveness in forecasting job trends.
This neural network analysis is a leap forward in understanding Boston’s economic dynamics, offering valuable insights for future planning and policy-making.
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